Besides these datasets that allow to investigate different aspects of face recognition (occlusion, expression, and pose), other larger datasets are often used for evaluation.
The Good, the Bad & the Ugly (GBU) dataset [1]} consists of 8'638 frontal images from 782 different identities.
It provides three protocols that mainly evaluate different illumination conditions called Good, Bad, and Ugly, where Ugly is the most difficult protocol, while Good is the easiest.
The IARPA Janus Benchmark C (IJB-C) [2]} is currently the most widely used benchmark for face recognition.
IJB-C has the highest diversity in occlusion, occupation, and geographic origin, and image quality to better represent as much of the world's population as possible.
The dataset consists of a total of 31'334 images and 11'779 videos of 3'531 identities.
